Originally posted on December 3, 2018 @ 9:45 AM
There is a huge chasm between three things: the intent and design (assumed philosophy) of a model, the semiotic diffusion of the model and what humans make of the model.
Models and symbols are not neutral nor objective. All models are semiotics and as such seek to explain the inexplicable. This is why when humans can’t explain something, they search for metaphor for meaning (Ricoeur 1975 The Rule of Metaphor). The search for meaning in metaphor and symbol is called ‘semiosis’. Most people don’t even realize when they are doing it.
The construction of models in safety is the search for meaning in seeking to explain risk, which is inexplicable because it is an expression of faith. All risk involves a leap of faith. There is no predictive analytics or future proofing and such delusional language simply demonstrates human futility with the constrains of fallibility (https://www.humandymensions.com/product/fallibility-risk-living-uncertainty/ ).
So, when science, technology, engineering and maths (STEM) seek certainty about the uncertainty of risk we usually end up with a semiotic (symbolic model) that such disciplines know little about. Then STEM naively seeks to objectivity the model and is believed by Safety through Fundamental Attribution Error (https://en.wikipedia.org/wiki/Fundamental_attribution_error) and objectivized in curriculum. We see this exemplified in the coloured risk matrix, Heinrich pyramid, Bradley Curve, swiss cheese, bow tie and countless other models put forward in search of meaning in risk. Even the effect of the psychology of colour on the unconscious is never considered in the construction and use of these silly models.
This is why it is so easy to set off a fury of debate about any risk assessment model. They are just models and may be helpful in that they provide theatre and a focus for discussion/debate about risk but of themselves are of no value in helping Due Diligence. If we took any of these models away it wouldn’t make a scrap of difference to Due Diligence.
The first step in getting the best out of a model is to know the nature of models and semiotics. We need to know the purpose of the model and its hidden philosophy. The search for meaning in design should be openly declared and assumptions well articulated. I have never seen such in any of the common risk management models on the market.